21 research outputs found
The tumor suppressor TERE1 (UBIAD1) prenyltransferase regulates the elevated cholesterol phenotype in castration resistant prostate cancer by controlling a program of ligand dependent SXR target genes.
Castrate-Resistant Prostate Cancer (CRPC) is characterized by persistent androgen receptor-driven tumor growth in the apparent absence of systemic androgens. Current evidence suggests that CRPC cells can produce their own androgens from endogenous sterol precursors that act in an intracrine manner to stimulate tumor growth. The mechanisms by which CRPC cells become steroidogenic during tumor progression are not well defined. Herein we describe a novel link between the elevated cholesterol phenotype of CRPC and the TERE1 tumor suppressor protein, a prenyltransferase that synthesizes vitamin K-2, which is a potent endogenous ligand for the SXR nuclear hormone receptor. We show that 50% of primary and metastatic prostate cancer specimens exhibit a loss of TERE1 expression and we establish a correlation between TERE1 expression and cholesterol in the LnCaP-C81 steroidogenic cell model of the CRPC. LnCaP-C81 cells also lack TERE1 protein, and show elevated cholesterol synthetic rates, higher steady state levels of cholesterol, and increased expression of enzymes in the de novo cholesterol biosynthetic pathways than the non-steroidogenic prostate cancer cells. C81 cells also show decreased expression of the SXR nuclear hormone receptor and a panel of directly regulated SXR target genes that govern cholesterol efflux and steroid catabolism. Thus, a combination of increased synthesis, along with decreased efflux and catabolism likely underlies the CRPC phenotype: SXR might coordinately regulate this phenotype. Moreover, TERE1 controls synthesis of vitamin K-2, which is a potent endogenous ligand for SXR activation, strongly suggesting a link between TERE1 levels, K-2 synthesis and SXR target gene regulation. We demonstrate that following ectopic TERE1 expression or induction of endogenous TERE1, the elevated cholesterol levels in C81 cells are reduced. Moreover, reconstitution of TERE1 expression in C81 cells reactivates SXR and switches on a suite of SXR target genes that coordinately promote both cholesterol efflux and androgen catabolism. Thus, loss of TERE1 during tumor progression reduces K-2 levels resulting in reduced transcription of SXR target genes. We propose that TERE1 controls the CPRC phenotype by regulating the endogenous levels of Vitamin K-2 and hence the transcriptional control of a suite of steroidogenic genes via the SXR receptor. These data implicate the TERE1 protein as a previously unrecognized link affecting cholesterol and androgen accumulation that could govern acquisition of the CRPC phenotype
Executive summary of the 2018 KDIGO Hepatitis C in CKD Guideline: welcoming advances in evaluation and management
No abstrac
Metabotyping of docosahexaenoic acid - Treated alzheimer's disease cell model
10.1371/journal.pone.0090123PLoS ONE92-POLN
Discriminatory marker metabolites identified from medium and lysate samples of DHA-treated and vehicle-treated CHO-wt and CHO-AβPP<sub>695</sub> cells.
a<p>Metabolite identification using standard compound.</p>b<p>Metabolite identification using NIST library search.</p>c<p>Normalized peak area values expressed as mean ± S.E.M.</p>d<p>Fold change (Δ): CHO-AβPP<sub>695 (treatment)/</sub>CHO-wt <sub>(treatment)</sub>.</p><p>*<i>p</i><0.05 and <sup>ns</sup> not significant when calculated using the independent <i>t</i>-test with Welch’s correction for normalized peak area of CHO-AβPP<sub>695</sub> cells compared to CHO-wt cells for respective treatment groups.</p><p>Abbreviations: DHA – docosahexaenoic acid, TCA – tricarboxylic acid.</p
PLS-DA score plot and validation plot for lysate samples.
<p>(A) PLS-DA score plot of vehicle-treated CHO-wt and CHO-AβPP<sub>695</sub> lysate samples (R<sup>2</sup>X = 0.474; R<sup>2</sup>Y = 0.985; Q<sup>2</sup> (cum) = 0.808; LV = 2); (B) Validation plot of the PLS-DA model obtained from 100 permutation tests for vehicle-treated lysate samples; (C) PLS-DA score plot of DHA-treated CHO-wt and CHO-AβPP<sub>695</sub> lysate samples (R<sup>2</sup>X = 0.645; R<sup>2</sup>Y = 0.993; Q<sup>2</sup> (cum) = 0.971; LV = 2); (D) Validation plot of the PLS-DA model obtained from 100 permutation tests for DHA-treated lysate samples.</p
Metabolites, their associated metabolic pathways and biological relevance in AD.
a<p>Metabolites are grouped together on the basis of their biological relevance. (↑) elevated in AD and (↓) reduced in AD.</p>b<p>Related to metabolites using KEGG database.</p><p>Abbreviations: DHA – docosahexaenoic acid, TCA – tricarboxylic acid.</p
Model validation for CHO-wt and CHO-AβPP<sub>695</sub> cells and effect of DHA on Aβ<sub>40</sub> release.
<p>(A) Conditioned medium was collected from CHO-wt and CHO-AβPP<sub>695</sub> cells with and without DHA treatment and subjected to ELISA immunoassays for Aβ<sub>40.</sub> There was negligible release of Aβ<sub>40</sub> from CHO-wt cells as compared to CHO-AβPP<sub>695</sub> cells at 24 and 48 h. A significant decrease was observed in the release of Aβ<sub>40</sub> in CHO-AβPP<sub>695</sub> cells after treatment with 25 µM DHA for 24 h and 48 h. <sup>#</sup><i>p</i><0.001 as compared to CHO-wt vehicle treated cells, <sup>φ</sup><i>p</i><0.05 compared to CHO-AβPP<sub>695</sub> 24 h vehicle treatment and <sup>§</sup><i>p</i><0.001 as compared to CHO-AβPP<sub>695</sub> 48 h vehicle treatment. Analysis was done via ANOVA with Bonferroni’s post-hoc analysis. (B) Western blot analysis of the cell lysates confirm AβPP<sub>695</sub> plasmid overexpression in CHO-AβPP<sub>695</sub> cells compared to CHO-wt.</p
Overlay of GC/TOFMS chromatograms.
<p>(A) Representative GC/TOFMS chromatogram of DHA-treated and vehicle-treated CHO-AβPP<sub>695</sub> cells – lysate (L) and medium (M) samples (B) Representative chromatogram demonstrating discriminatory metabolites between vehicle-treated and DHA-treated CHO-wt cells and CHO-AβPP<sub>695</sub> cells.</p
PLS-DA score plot and validation plot for medium samples.
<p>(A) PLS-DA score plot of vehicle-treated CHO-wt and CHO-AβPP<sub>695</sub> medium samples (R<sup>2</sup>X = 0.679; R<sup>2</sup>Y = 0.994; Q<sup>2</sup> (cum) = 0.929; LV = 3); (B) Validation plot of the PLS-DA model obtained from 100 permutation tests for vehicle-treated medium samples; (C) PLS-DA score plot of DHA-treated CHO-wt and CHO-AβPP<sub>695</sub> medium samples (R<sup>2</sup>X = 0.745; R<sup>2</sup>Y = 0.992; Q<sup>2</sup> (cum) = 0.885; LV = 3); (D) Validation plot of the PLS-DA model obtained from 100 permutation tests for DHA-treated medium samples.</p